I am plotting Validation Curves using the Yellowbrick package here.
I am using a Regressor model, and so naturally, my score of interest is MSE (or neg_mean_squared_error as the actual parameter). The example code in the documentation uses R^2, so there is no need to flip the sign when plotting those Validation curves.
Therefore, I was wondering how to flip the sign for the Validation loss curves? My code reproduced using the Yellowbrick template is here:
import numpy as np
from yellowbrick.datasets import load_energy
from yellowbrick.model_selection import ValidationCurve
from sklearn.tree import DecisionTreeRegressor
# Load a regression dataset
X, y = load_energy()
viz = ValidationCurve(
DecisionTreeRegressor(), param_name="max_depth",
param_range=np.arange(1, 11), cv=10, scoring="neg_mean_squared_error"
)
# Fit and show the visualizer
viz.fit(X, y)
viz.show()
Want something like this except flipped since these will be loss curves as opposed to R^2 curves:
